Overview

Dataset statistics

Number of variables14
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory117.9 B

Variable types

Numeric3
Text3
Categorical7
DateTime1

Dataset

Description객체id,현황도형 관리번호,도형 대분류코드,도형 중분류코드,도형 소분류코드,도형 속성코드,도형 조서관리 코드,결정고시관리코드,라벨명,시군구코드,도면번호,현황도형 생성일시,면적(도형),길이(도형)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21135/S/1/datasetView.do

Alerts

도형 대분류코드 has constant value ""Constant
도형 중분류코드 has constant value ""Constant
도형 소분류코드 has constant value ""Constant
도형 속성코드 has constant value ""Constant
시군구코드 is highly overall correlated with 결정고시관리코드High correlation
결정고시관리코드 is highly overall correlated with 라벨명 and 1 other fieldsHigh correlation
라벨명 is highly overall correlated with 결정고시관리코드High correlation
면적(도형) is highly overall correlated with 길이(도형)High correlation
길이(도형) is highly overall correlated with 면적(도형)High correlation
결정고시관리코드 is highly imbalanced (83.5%)Imbalance
라벨명 is highly imbalanced (86.1%)Imbalance
시군구코드 is highly imbalanced (88.9%)Imbalance
객체id has unique valuesUnique
현황도형 관리번호 has unique valuesUnique
도형 조서관리 코드 has unique valuesUnique
면적(도형) has unique valuesUnique
길이(도형) has unique valuesUnique

Reproduction

Analysis started2024-05-11 09:30:29.455567
Analysis finished2024-05-11 09:30:39.583234
Duration10.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10876.382
Minimum10617
Maximum10940
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T09:30:39.867725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10617
5-th percentile10620.35
Q110889.75
median10906.5
Q310923.25
95-th percentile10936.65
Maximum10940
Range323
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation95.549007
Coefficient of variation (CV)0.0087849989
Kurtosis3.6234645
Mean10876.382
Median Absolute Deviation (MAD)17
Skewness-2.2888712
Sum739594
Variance9129.6128
MonotonicityStrictly increasing
2024-05-11T09:30:40.459199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10617 1
 
1.5%
10917 1
 
1.5%
10923 1
 
1.5%
10922 1
 
1.5%
10921 1
 
1.5%
10920 1
 
1.5%
10919 1
 
1.5%
10918 1
 
1.5%
10916 1
 
1.5%
10908 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
10617 1
1.5%
10618 1
1.5%
10619 1
1.5%
10620 1
1.5%
10621 1
1.5%
10622 1
1.5%
10623 1
1.5%
10624 1
1.5%
10881 1
1.5%
10882 1
1.5%
ValueCountFrequency (%)
10940 1
1.5%
10939 1
1.5%
10938 1
1.5%
10937 1
1.5%
10936 1
1.5%
10935 1
1.5%
10934 1
1.5%
10933 1
1.5%
10932 1
1.5%
10931 1
1.5%

현황도형 관리번호
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T09:30:41.200378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters1632
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row11000UQ142PS202007220027
2nd row11000UQ142PS202007220028
3rd row11000UQ142PS202007220029
4th row11000UQ142PS202007220030
5th row11000UQ142PS202007220031
ValueCountFrequency (%)
11000uq142ps202007220027 1
 
1.5%
11000uq142ps202007220049 1
 
1.5%
11000uq142ps202007220044 1
 
1.5%
11000uq142ps202007220045 1
 
1.5%
11000uq142ps202007220046 1
 
1.5%
11000uq142ps202007220047 1
 
1.5%
11000uq142ps202007220048 1
 
1.5%
11000uq142ps202007220028 1
 
1.5%
11000uq142ps202007220001 1
 
1.5%
11000uq142ps202007220051 1
 
1.5%
Other values (58) 58
85.3%
2024-05-11T09:30:42.405302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 554
33.9%
2 352
21.6%
1 228
14.0%
4 88
 
5.4%
7 72
 
4.4%
U 68
 
4.2%
Q 68
 
4.2%
P 68
 
4.2%
S 68
 
4.2%
5 17
 
1.0%
Other values (4) 49
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1360
83.3%
Uppercase Letter 272
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 554
40.7%
2 352
25.9%
1 228
16.8%
4 88
 
6.5%
7 72
 
5.3%
5 17
 
1.2%
3 16
 
1.2%
6 16
 
1.2%
9 11
 
0.8%
8 6
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
U 68
25.0%
Q 68
25.0%
P 68
25.0%
S 68
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1360
83.3%
Latin 272
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 554
40.7%
2 352
25.9%
1 228
16.8%
4 88
 
6.5%
7 72
 
5.3%
5 17
 
1.2%
3 16
 
1.2%
6 16
 
1.2%
9 11
 
0.8%
8 6
 
0.4%
Latin
ValueCountFrequency (%)
U 68
25.0%
Q 68
25.0%
P 68
25.0%
S 68
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 554
33.9%
2 352
21.6%
1 228
14.0%
4 88
 
5.4%
7 72
 
4.4%
U 68
 
4.2%
Q 68
 
4.2%
P 68
 
4.2%
S 68
 
4.2%
5 17
 
1.0%
Other values (4) 49
 
3.0%

도형 대분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
UQT600
68 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQT600
2nd rowUQT600
3rd rowUQT600
4th rowUQT600
5th rowUQT600

Common Values

ValueCountFrequency (%)
UQT600 68
100.0%

Length

2024-05-11T09:30:43.023625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:43.356547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqt600 68
100.0%

도형 중분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
68
100.0%

Length

2024-05-11T09:30:43.710947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:44.158526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 소분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
68
100.0%

Length

2024-05-11T09:30:44.517025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:44.803575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 속성코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
UQT600
68 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQT600
2nd rowUQT600
3rd rowUQT600
4th rowUQT600
5th rowUQT600

Common Values

ValueCountFrequency (%)
UQT600 68
100.0%

Length

2024-05-11T09:30:45.299475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:45.737276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqt600 68
100.0%

도형 조서관리 코드
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T09:30:46.299382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1360
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row11000BTZ202007210028
2nd row11000BTZ202007210029
3rd row11000BTZ202007210030
4th row11000BTZ202007210032
5th row11000BTZ202007210033
ValueCountFrequency (%)
11000btz202007210028 1
 
1.5%
11000btz202007210051 1
 
1.5%
11000btz202007210046 1
 
1.5%
11000btz202007210047 1
 
1.5%
11000btz202007210048 1
 
1.5%
11000btz202007210049 1
 
1.5%
11000btz202007210050 1
 
1.5%
11000btz202007210029 1
 
1.5%
11000btz202007210001 1
 
1.5%
11000btz202007210053 1
 
1.5%
Other values (58) 58
85.3%
2024-05-11T09:30:47.618551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 557
41.0%
1 222
 
16.3%
2 220
 
16.2%
7 74
 
5.4%
B 68
 
5.0%
T 68
 
5.0%
Z 68
 
5.0%
5 17
 
1.2%
3 17
 
1.2%
4 17
 
1.2%
Other values (3) 32
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1156
85.0%
Uppercase Letter 204
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 557
48.2%
1 222
 
19.2%
2 220
 
19.0%
7 74
 
6.4%
5 17
 
1.5%
3 17
 
1.5%
4 17
 
1.5%
6 17
 
1.5%
9 8
 
0.7%
8 7
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
B 68
33.3%
T 68
33.3%
Z 68
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1156
85.0%
Latin 204
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 557
48.2%
1 222
 
19.2%
2 220
 
19.0%
7 74
 
6.4%
5 17
 
1.5%
3 17
 
1.5%
4 17
 
1.5%
6 17
 
1.5%
9 8
 
0.7%
8 7
 
0.6%
Latin
ValueCountFrequency (%)
B 68
33.3%
T 68
33.3%
Z 68
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 557
41.0%
1 222
 
16.3%
2 220
 
16.2%
7 74
 
5.4%
B 68
 
5.0%
T 68
 
5.0%
Z 68
 
5.0%
5 17
 
1.2%
3 17
 
1.2%
4 17
 
1.2%
Other values (3) 32
 
2.4%

결정고시관리코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
11000NTC202007210001
65 
 
1
11000NTC202209160001
 
1
11000NTC202403290004
 
1

Length

Max length20
Median length20
Mean length19.720588
Min length1

Unique

Unique3 ?
Unique (%)4.4%

Sample

1st row11000NTC202007210001
2nd row11000NTC202007210001
3rd row11000NTC202007210001
4th row11000NTC202007210001
5th row11000NTC202007210001

Common Values

ValueCountFrequency (%)
11000NTC202007210001 65
95.6%
1
 
1.5%
11000NTC202209160001 1
 
1.5%
11000NTC202403290004 1
 
1.5%

Length

2024-05-11T09:30:48.773616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:49.088938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11000ntc202007210001 65
97.0%
11000ntc202209160001 1
 
1.5%
11000ntc202403290004 1
 
1.5%

라벨명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
도시자연공원구역
66 
불암산 도시자연공원구역
 
1
인왕산도시자연공원구역
 
1

Length

Max length12
Median length8
Mean length8.1029412
Min length8

Unique

Unique2 ?
Unique (%)2.9%

Sample

1st row도시자연공원구역
2nd row도시자연공원구역
3rd row도시자연공원구역
4th row도시자연공원구역
5th row도시자연공원구역

Common Values

ValueCountFrequency (%)
도시자연공원구역 66
97.1%
불암산 도시자연공원구역 1
 
1.5%
인왕산도시자연공원구역 1
 
1.5%

Length

2024-05-11T09:30:49.631149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:50.181018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시자연공원구역 67
97.1%
불암산 1
 
1.4%
인왕산도시자연공원구역 1
 
1.4%

시군구코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
11000
67 
11590
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)1.5%

Sample

1st row11000
2nd row11000
3rd row11000
4th row11000
5th row11000

Common Values

ValueCountFrequency (%)
11000 67
98.5%
11590 1
 
1.5%

Length

2024-05-11T09:30:50.691990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:30:51.192971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11000 67
98.5%
11590 1
 
1.5%

도면번호
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T09:30:51.841080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8676471
Min length1

Characters and Unicode

Total characters127
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)97.1%

Sample

1st row28
2nd row29
3rd row30
4th row32
5th row33
ValueCountFrequency (%)
68 1
 
1.5%
15 1
 
1.5%
13 1
 
1.5%
12 1
 
1.5%
11 1
 
1.5%
9 1
 
1.5%
8 1
 
1.5%
7 1
 
1.5%
28 1
 
1.5%
14 1
 
1.5%
Other values (56) 56
84.8%
2024-05-11T09:30:53.077708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 17
13.4%
4 17
13.4%
5 17
13.4%
1 17
13.4%
2 16
12.6%
6 15
11.8%
8 7
5.5%
7 7
5.5%
0 6
 
4.7%
9 6
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 125
98.4%
Space Separator 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 17
13.6%
4 17
13.6%
5 17
13.6%
1 17
13.6%
2 16
12.8%
6 15
12.0%
8 7
5.6%
7 7
5.6%
0 6
 
4.8%
9 6
 
4.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 17
13.4%
4 17
13.4%
5 17
13.4%
1 17
13.4%
2 16
12.6%
6 15
11.8%
8 7
5.5%
7 7
5.5%
0 6
 
4.7%
9 6
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 17
13.4%
4 17
13.4%
5 17
13.4%
1 17
13.4%
2 16
12.6%
6 15
11.8%
8 7
5.5%
7 7
5.5%
0 6
 
4.7%
9 6
 
4.7%

현황도형 생성일시
Date

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2020-07-21 00:00:00
Maximum2024-04-15 00:00:00
2024-05-11T09:30:53.551490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:53.924447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

면적(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1024577.1
Minimum2159.3499
Maximum12505950
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T09:30:54.444116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2159.3499
5-th percentile10481.433
Q161420.575
median203093.27
Q3805863.67
95-th percentile4670217.1
Maximum12505950
Range12503791
Interquartile range (IQR)744443.09

Descriptive statistics

Standard deviation2036333.3
Coefficient of variation (CV)1.9874867
Kurtosis15.40752
Mean1024577.1
Median Absolute Deviation (MAD)173988.82
Skewness3.5173941
Sum69671241
Variance4.1466535 × 1012
MonotonicityNot monotonic
2024-05-11T09:30:54.932502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111515.419412 1
 
1.5%
1646579.94721 1
 
1.5%
12505950.1063 1
 
1.5%
541914.121168 1
 
1.5%
2075024.60315 1
 
1.5%
1045261.04196 1
 
1.5%
4257325.46338 1
 
1.5%
7069571.95069 1
 
1.5%
752512.729417 1
 
1.5%
1656439.41181409 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
2159.34992281 1
1.5%
2247.70087359 1
1.5%
4125.97831399 1
1.5%
9886.51129577 1
1.5%
11586.2876361 1
1.5%
13226.9023552 1
1.5%
13438.3350209 1
1.5%
18333.1730029 1
1.5%
26074.3459438 1
1.5%
32134.5693389 1
1.5%
ValueCountFrequency (%)
12505950.1063 1
1.5%
7069571.95069 1
1.5%
4989382.07454 1
1.5%
4892543.3545053 1
1.5%
4257325.46338 1
1.5%
4185397.26482 1
1.5%
3721692.46702 1
1.5%
3611661.10914 1
1.5%
2890392.53442 1
1.5%
2075024.60315 1
1.5%

길이(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9278.6339
Minimum273.54031
Maximum73795.991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T09:30:55.353899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum273.54031
5-th percentile639.69647
Q11979.8959
median5105.8597
Q313277.794
95-th percentile24917.506
Maximum73795.991
Range73522.451
Interquartile range (IQR)11297.899

Descriptive statistics

Standard deviation11856.031
Coefficient of variation (CV)1.2777776
Kurtosis13.369163
Mean9278.6339
Median Absolute Deviation (MAD)3798.8792
Skewness3.1294153
Sum630947.1
Variance1.4056546 × 108
MonotonicityNot monotonic
2024-05-11T09:30:55.894967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4552.7808112 1
 
1.5%
13956.6552677 1
 
1.5%
73795.9914848 1
 
1.5%
5577.24711844 1
 
1.5%
25346.7675625 1
 
1.5%
11768.5184971 1
 
1.5%
47070.8102899 1
 
1.5%
16304.9030784 1
 
1.5%
11836.2426172 1
 
1.5%
13858.69822224 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
273.5403121 1
1.5%
367.83138223 1
1.5%
618.53370661 1
1.5%
634.48646848 1
1.5%
649.37218565 1
1.5%
664.05636895 1
1.5%
956.65809342 1
1.5%
978.55593074 1
1.5%
991.41380415 1
1.5%
1214.72504001 1
1.5%
ValueCountFrequency (%)
73795.9914848 1
1.5%
47070.8102899 1
1.5%
32432.8775269 1
1.5%
25346.7675625 1
1.5%
24120.30460476 1
1.5%
22175.7695985 1
1.5%
22146.6021135 1
1.5%
21028.082044 1
1.5%
19692.1674599 1
1.5%
19274.8875553 1
1.5%

Interactions

2024-05-11T09:30:37.238297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:34.883626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:36.305316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:37.660939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:35.348888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:36.615777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:38.062461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:35.958083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:30:36.917070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T09:30:56.316368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id현황도형 관리번호도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
객체id1.0001.0001.0000.0000.0000.0000.8820.0000.0000.000
현황도형 관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도형 조서관리 코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
결정고시관리코드0.0001.0001.0001.0001.0001.0000.0001.0000.3740.498
라벨명0.0001.0001.0001.0001.0000.0000.0001.0000.6770.568
시군구코드0.0001.0001.0001.0000.0001.0001.0001.0000.0000.000
도면번호0.8821.0001.0000.0000.0001.0001.0000.0000.0000.000
현황도형 생성일시0.0001.0001.0001.0001.0001.0000.0001.0000.3740.498
면적(도형)0.0001.0001.0000.3740.6770.0000.0000.3741.0000.798
길이(도형)0.0001.0001.0000.4980.5680.0000.0000.4980.7981.000
2024-05-11T09:30:56.751241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드결정고시관리코드라벨명
시군구코드1.0000.9850.000
결정고시관리코드0.9851.0000.992
라벨명0.0000.9921.000
2024-05-11T09:30:57.105423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id면적(도형)길이(도형)결정고시관리코드라벨명시군구코드
객체id1.0000.2880.2150.0000.0000.000
면적(도형)0.2881.0000.9510.2450.3540.000
길이(도형)0.2150.9511.0000.3570.4440.000
결정고시관리코드0.0000.2450.3571.0000.9920.985
라벨명0.0000.3540.4440.9921.0000.000
시군구코드0.0000.0000.0000.9850.0001.000

Missing values

2024-05-11T09:30:38.569247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T09:30:39.199140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
01061711000UQ142PS202007220027UQT600UQT60011000BTZ20200721002811000NTC202007210001도시자연공원구역11000282020-07-22 00:00:00.0111515.4194124552.780811
11061811000UQ142PS202007220028UQT600UQT60011000BTZ20200721002911000NTC202007210001도시자연공원구역11000292020-07-22 00:00:00.033138.2461042090.23923
21061911000UQ142PS202007220029UQT600UQT60011000BTZ20200721003011000NTC202007210001도시자연공원구역11000302020-07-22 00:00:00.085071.6509854447.44533
31062011000UQ142PS202007220030UQT600UQT60011000BTZ20200721003211000NTC202007210001도시자연공원구역11000322020-07-22 00:00:00.0220129.0358357367.253032
41062111000UQ142PS202007220031UQT600UQT60011000BTZ20200721003311000NTC202007210001도시자연공원구역11000332020-07-22 00:00:00.0210333.4468633172.876456
51062211000UQ142PS202007220032UQT600UQT60011000BTZ20200721003411000NTC202007210001도시자연공원구역11000342020-07-22 00:00:00.052640.106751967.6062
61062311000UQ142PS202007220033UQT600UQT60011000BTZ20200721003511000NTC202007210001도시자연공원구역11000352020-07-22 00:00:00.0833072.23904119250.740849
71062411000UQ142PS202007220034UQT600UQT60011000BTZ20200721003611000NTC202007210001도시자연공원구역11000362020-07-22 00:00:00.0539542.87538313098.623836
81088111000UQ142PS202007220051UQT600UQT60011000BTZ20200721005311000NTC202007210001도시자연공원구역11000532020-07-22 00:00:00.0449157.961326674.245269
91088211000UQ142PS202007220035UQT600UQT60011000BTZ20200721003711000NTC202007210001도시자연공원구역11000372020-07-22 00:00:00.0487507.99950612896.256135
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
581093111000UQ142PS202007220017UQT600UQT60011000BTZ20200721001911000NTC202007210001도시자연공원구역11000192020-07-22 00:00:00.0146438.5614485426.423501
591093211000UQ142PS202007220019UQT600UQT60011000BTZ20200721002111000NTC202007210001도시자연공원구역11000212020-07-22 00:00:00.0149812.1507123517.4542
601093311000UQ142PS202007220020UQT600UQT60011000BTZ20200721002211000NTC202007210001도시자연공원구역11000222020-07-22 00:00:00.0236009.5335387394.067526
611093411000UQ142PS202007220021UQT600UQT60011000BTZ20200721002311000NTC202007210001도시자연공원구역11000232020-07-22 00:00:00.09886.511296978.555931
621093511000UQ142PS202007220022UQT600UQT60011000BTZ20200721002411000NTC202007210001도시자연공원구역11000242020-07-22 00:00:00.0111441.3494281988.234689
631093611000UQ142PS202007220023UQT600UQT60011000BTZ20200721002511000NTC202007210001도시자연공원구역11000252020-07-22 00:00:00.0538202.5717836305.7044
641093711000UQ142PS202007220024UQT600UQT60011000BTZ20200721002611000NTC202007210001도시자연공원구역11000262020-07-22 00:00:00.032134.569339956.658093
651093811000UQ142PS202007220025UQT600UQT60011000BTZ20200721003111000NTC202007210001도시자연공원구역11000312020-07-22 00:00:00.0281830.0769265107.575303
661093911000UQ142PS202007220026UQT600UQT60011000BTZ20200721002711000NTC202007210001도시자연공원구역11000272020-07-22 00:00:00.0234747.6021834088.334065
671094011000UQ142PS202007220018UQT600UQT60011000BTZ20200721002011000NTC202007210001도시자연공원구역11000202020-07-22 00:00:00.0203243.8699345104.144173